Evidence map›Paper›PMID 30798436›Full record

ArticleMolecular diversity2020

Combining ligand- and structure-based in silico methods for the identification of natural product-based inhibitors of Akt1.

Priya Mahajan, Bhumika Wadhwa, Manas Ranjan Barik, Fayaz Malik, Amit Nargotra

Open access · bronzeAbstract read
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In one paragraph

Article in Molecular diversity, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 30% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Ellagic Acid, Kaempferol, and Quercetin fromCurrent pharmacology reports · 2019
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Priya MahajanDiscovery Informatics Division, CSIR-Indian Institute of Integrative Medicine, Canal Road, Jammu, 180001, India.
Bhumika WadhwaCancer Pharmacology Division, CSIR-Indian Institute of Integrative Medicine, Canal Road, Jammu, 180001, India.
Manas Ranjan BarikDiscovery Informatics Division, CSIR-Indian Institute of Integrative Medicine, Canal Road, Jammu, 180001, India.
Fayaz MalikCancer Pharmacology Division, CSIR-Indian Institute of Integrative Medicine, Canal Road, Jammu, 180001, India.
Amit NargotraDiscovery Informatics Division, CSIR-Indian Institute of Integrative Medicine, Canal Road, Jammu, 180001, India. anargotra@iiim.ac.in.ORCID http://orcid.org/0000-0003-3561-219X
Indian Institute of Integrative Medicine · IN

Funding

Department of Biotechnology, Ministry of Science and Technology GAP0141
6 · The paper itself

Abstract

The traditional method of drug discovery process has been surpassed by a rational approach where computer-aided drug designing plays a vital role in the identification of leads from large compound databases. Further, natural products have an important role in drug discovery as these have been the source of most active ingredients of medicines. Herein, in silico structure- and ligand-based approaches have been applied to screen in-house IIIM natural product repository for Akt1 (serine/threonine protein kinases) which is a well-known therapeutic target for cancer due to its overexpression and preventing the cells from undergoing apoptosis. Combined ligand-based and structure-based strategies were applied on to the existing library comprising of about 700 pure natural products, and the compounds identified from screening were biologically evaluated for Akt1 inhibition using Akt1 kinase activity assay. Fourteen promising compounds showed significant inhibition at 500 nM through in vitro screening, and from them, eight were new for Akt1 inhibition. Through the MD studies of Akt1 with the most active compound IN00145, it was inferred that Lys179, Glu191, Glu228, Ala230, Glu234 and Asp292 are the important amino acid residues which provide stability to the Akt1-IN00145 complex. Lead optimization studies were also performed around the actives to design better and selective inhibitors for Akt1. The results emphasized the successful application of virtual screening to identify new Akt1 inhibitor scaffolds that can be developed into a drug candidate in drug discovery programme.

Indexed as

Drug DesignMolecular Docking SimulationMolecular Dynamics SimulationBiological ProductsDrug DiscoveryDrug Evaluation, PreclinicalHumansLigandsMolecular ConformationProtein Kinase InhibitorsProto-Oncogene Proteins c-aktQuantitative Structure-Activity RelationshipROC CurveAKT1 protein, humanBiological ProductsLigandsProtein Kinase InhibitorsProto-Oncogene Proteins c-aktAkt1Akt1 inhibitorsCancerIn silico screeningLead optimizationMolecular dynamicsNatural product

Identifiers

PMID30798436
OpenAlexW2915447301

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.